Modern data centers often have a multi-tier configuration wherein a front end server accesses one or more layers of middle-tier and back-tier servers for various services. One example of a back-end server is a storage array. Storage arrays form the backbone of modern data centers by providing consolidated data access to multiple applications simultaneously. Increasingly, organizations are moving towards consolidated storage, either using block-based access over a Storage Area Network (SAN) or file-based access over Network-Attached Storage (NAS) systems. A Storage Area Network is a network whose primary purpose is the transfer of data between computer systems and storage elements. Easy access from anywhere at anytime, ease of backup, flexibility in allocation and centralized administration are some of the advantages of storage arrays.
Quality of Service (QoS) refers to resource management methodologies whereby resources are allocated among a plurality of users or clients according to a policy. The policy may guarantee a minimum and/or maximum level of service (e.g., as a percentage of resources). It is also common to distribute services according to an assigned resource “shares,” which are alternatively referred to in literature as “weights,” so that each client is provided a level of service that compares to its peers at the same ratio as the assigned shares. In addition, combinations of these policies are possible. Thus, QoS suggests an ability to evenly distribute services or arbitrarily assign priority to selected applications, users, or data flows.
In the field of computer networking, QoS has been implemented to provide a guaranteed minimum bit rate, delay, jitter, packet dropping probability, or error rate. For example, in the case of TCP based QoS, a host may try to control dataflow based on round trip time (RTT) and packet loss probability. In TCP, the RTT is the elapsed time from the transmission of a packet to receipt of an acknowledgement by the recipient. The RTT effectively measures the delay imposed by the intervening, generally stateless, network. Packet loss probability is the percentage of packets for which acknowledgements were not received within a given period of time. Packets may be lost at any point along the transmission path from the host to the recipient, due to any number of factors such as oversaturation of network switches, corrupted packets rejected in-transit, etc.
Because there are significant differences between TCP and middle tier/back end servers, the techniques known for providing QoS management of TCP data flows over a network are not directly applicable to middle tier and back end servers. For some back-end servers, it is simple to provide a centralized QoS management mechanism at the server itself, to guarantee each client its assigned share of resources. However in some types of servers, such as in appliances such as storage arrays, the servers appear as black boxes to the clients and are therefore not easily (or at all) configurable for QoS.
With regard to storage array management, most existing solutions provide bandwidth allocation among multiple applications running on a single host. In that case, one centralized scheduler has complete control over requests going to the storage systems. Other approaches try to control the queue length at the array to provide tight latency control, but they are also centralized. In a distributed case, throttling based approaches such as Hewlett-Packard's “Triage” system for storage QoS have been proposed. Such host-based throttling solutions use centralized monitoring and work at a very coarse granularity which may cause substantial loss in utilization. Running them at finer granularity may cause a prohibitive increase in communication costs. In general, strict throttling solutions lead to efficiency losses and non work-conserving behavior.